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Exosomes: Supramolecular Biomarker Conduit in Cancer

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Computational Intelligence in Oncology

Part of the book series: Studies in Computational Intelligence ((SCI,volume 1016))

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Abstract

Cancer is a complex disease attributed to genetic distortions and cellular and non-cellular host responses. Tumors contain a variety of cell types that interact in a dynamic manner to maintain cancer-specific signaling networks. Extrinsic vesicles (EVs) are formed and retrieved as part of cell communication. Even tumor cells release exosomes, which are “30–100 nm” membrane vesicles that come from endosomes. Parental cells proteins and nucleic acids enrich their repertoire, and intercellular signals are thought to be transmitted by them. DNA and RNA are released into all body fluids as well as protein biomarkers that can be used to identify tumors and therapeutic targets. Patients with cancer may be screened for tumors based on the presence of exosomes secreted by tumor cells. Biomarkers for clinical diagnoses, such as exosomal proteins and microRNAs, are attracting considerable interest. The unique biogenesis of exosomes, their pervasive production by all cell types, and their biological features in liquid biopsy samples have all contributed to a growing interest in exosomes as cancer biomarkers. Cancer ‘prognosis’, ‘diagnosis’ and ‘progression’ may be more comprehensively assessed using these biomarkers, which reflect the heterogeneous biological changes associated with tumor growth. This chapter provides a brief overview of exosomal initiation, function, isolation, and the current roles of computation in oncology in the context of multi-omic technologies.

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Authors and Affiliations

  1. Department of Microbiology, Punjab Agricultural University, Ludhiana, 141004, India

    Manmeet Kaur & H. S. Sodhi

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  1. Manmeet Kaur
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  2. H. S. Sodhi
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Correspondence to Manmeet Kaur .

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  1. Department of Computer Science, Jamia Millia Islamia, New Delhi, India

    Khalid Raza

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Kaur, M., Sodhi, H.S. (2022). Exosomes: Supramolecular Biomarker Conduit in Cancer. In: Raza, K. (eds) Computational Intelligence in Oncology. Studies in Computational Intelligence, vol 1016. Springer, Singapore. https://doi.org/10.1007/978-981-16-9221-5_18

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